Improving Operations of Methanol Refining

Abstract

Improving the operations of a high purity, multi-component industrial methanol distillation unit is a fine balancing act. On one hand, the operators need to ensure the ethanol impurities in distillate methanol stream are kept below the federal AA grade specification of 10 ppm. On the other hand, the operators need to maintain an adequate product recovery rate ( ) of 97.5 %+ for an economically favourable operation. In current operations, with a lack of advanced controls present, the operators have no other choice than to use excess reboiler duty to offset effects of complex process dynamics and maintain these demanding specifications, limiting the levels of product recovery, reducing column throughput and/or stability. This thesis describes the author’s investigation into how better process control and operational changes can improve the product recovery, stability and energy efficiency of these columns. To achieve these objectives, a validated process simulation of an industrial methanol distillation column was built using commercially available software. A steady state analysis of the column confirmed that the column can be operated at a of 99.5 %+, and that lowering the side draw location and reducing the side draw flow rate can improve energy efficiency. Analysis of the column dynamics showed that the ethanol profile forms a bulge near the side draw that needs to be explicitly managed. A novel, practical control scheme was developed to detect and manage the ethanol bulge movement. This control scheme was able to maintain on specification operations during process disturbances with normal levels of reboiler duty, while a standard DV control structure was unable to maintain specification. The proposed control scheme however, does not monitor or control . To operate the column at a of 99.5 %+, a new control structure that explicitly controls both and product purity was necessary. A novel, practical control scheme based on override logic was developed for this purpose and its performance was compared with a model predictive control (MPC) setup. During disturbance tests, both controllers maintained on-specification product at of 99.6 %, although the MPC was slightly more energy efficient. Further analysis showed a multitude of economic and practical factors that need to be considered in deciding between the two control schemes. To successfully implement in industry the controls suggested in this thesis, it is necessary to capture all the cost and benefits of these controls (operations).